The following includes information that may be useful in understanding the present inventions. It is not an admission that any of the information provided herein is prior art, or relevant, to the presently described or claimed inventions, or that any publication or document that is specifically or implicitly referenced is prior art.
One recent technological focus in the field of human genomics is pharmacogenomics, which includes efforts to use human DNA sequence variability in the development and prescription of drugs. Pharmacogenomics is based on the correlation or association between a given genotype and a resulting phenotype. Since the first correlation study over half-a-century ago linking adverse drug response with amino acid variations in two drug-metabolizing enzymes (plasma cholinesterase and glucose-6-phosphate dehydrogenase), various studies have reported on sequence polymorphisms within drug metabolism enzymes, drug targets and drug transporters and correlations with compromised levels of drug efficacy or safety.
Pharmacogenomics information will be especially useful in clinical settings where correlation information can be used to prevent drug toxicities, or develop treatment regimes. For example, patients are often screened for genetic differences in the thiopurine methyltransferase gene that cause decreased metabolism of 6-mercaptopurine or azathiopurine. However, only a small percentage of observed drug toxicities have been explained adequately by the set of pharmacogenomic markers available to date.
In addition, “outlier” individuals, or individuals experiencing unanticipated effects in clinical trials (when administered drugs that have previously been demonstrated to be both safe and efficacious), can cause substantial delays in obtaining FDA drug approval and may even cause certain drugs to come off market, though such drugs may be efficacious for a majority of recipients.
Biotechnological methods used to date to identify target genomic regions include, for example, differential gene expression (which essentially looks for differences in gene expression between control and case samples); protein-protein interaction maps which are used to identify drug receptors and their immediate effectors; and mining human sequence databases for sequences similar to known disease-related, pharmacokinetic or pharmacodynamic regulators. In comparison, association studies that correlate and validate genomic regions with a particular phenotypic trait rely on population genetics and robust statistical metrics. Association studies provide a powerful tool to obtain greater amounts of information in a shorter amount of time thus reducing costs of research and development efforts.
Because all humans are 99.9% identical in their genetic makeup, the DNA sequence of any two individuals is nearly identical. Variations between individuals include, for example, deletions or insertions of DNA sequences, variations in the number of repetitive DNA elements in non-coding regions and changes in a single nucleotide position, or “single nucleotide polymorphisms” (SNP).
SNPs are useful for conducting association studies, and have been identified as potentially useful genetic markers for phenotypic traits. Phenotypic traits of particular interest to the medical field include predisposition to disease, and response to a particular drug or treatment regime.
For example, recent studies report that the response to the antiplatelet agent clopidogrel is variable, with 20-40% of patients being classified as poor responders or resistant to clopidogrel due to low inhibition of ADP-induced platelet aggregation or activation (Angiolillo D J et al. (2005); Gurbel P A et al. (2003); Gurbel P A et al. (2006); Gurbel P A, Bliden, K P, Hayes K M et al. (2005); Mobley, J E et al. (2004); and Muller I et al. (2003)). Metabolising enzymes (e.g. cytochrome CYP450 system) and gut absorptive mechanisms (e.g. p-glycoprotein efflux pump) may be responsible for this variability. The activity of CYP3A4, measured by radiolabelled erythromycin breath testing, has reportedly been correlated with the response to clopidogrel (Lau W C et al.). CYP3A4 is reportedly responsible for the metabolism of most drugs and it has been believed that this pathway is a main limiting factor for biotransforming clopidogrel into its active metabolite.
However clopidogrel's metabolism may be influenced also by CYP2C19, CYP2C9 and possibly CYP3A5 (Brandt J T, Close S L et al. (2007) and Suh J H et al. (2006)). A number of well described genetic polymorphisms exist within the genes for these enzymes that render individuals either poor-metabolisers or ultra-metabolisers. For instance the common CYP2C19*2 allele displays a loss of function of this enzyme, and carriers have been reported to show a reduced antiplatelet response to 75 mg once daily of clopidogrel (Hulot J S et al. (2006) and Fontana P, Senouf D et al. (2007)) and a 300 mg loading dose (Brandt J T, Close S L et al (2007)). A CYP3A4 polymorphism has also been reported as associated with a reduced response to 300 mg of clopidogrel (Angiolillo D J et al. (2006); and Fontana P, Hulot J S et al (2006)). A CYP3A5 loss of function genotype *3 has been reported to be associated with increased atherothrombotic events in individuals after percutaneous coronary intervention (PCI) (Suh J H et al. (2006))
The pharmacokinetic component of the ISAR-CHOICE study suggested that the ceiling effect with clopidogrel 600 mg might be due to saturable intestinal absorption of the drug (von Beckerath N et al. (2005)). It was subsequently proposed that the p-glycoprotein efflux pump may be implicated in this process. Furthermore a polymorphism of the ABCB1 gene (C3435T), coding for p-glycoprotein, has been reported to reduce plasma parent drug levels (Taubert D et al.) However, this result has not been translated into a pharmacodynamic effect.
A lower pharmacodynamic response has reportedly been linked to a higher relative risk of adverse cardiac events in several clinical studies, suggesting that a reduced pharmacodynamic response to clopidogrel is clinically relevant (Ajzenberg, N, et al. (2005); Barragan, P et al. (2003); Cuisset, T et al. (2006); Gurbel, P A, Bliden, K P, Samara, W et al. (2005); Gurbel, P A, Bliden, K P, Guyer, K et al. (2005) and Matetzky, S et al. (2004)).
Response to clopidogrel displays wide inter-individual variability and a number of individuals show no or minimal response to the drug. Importantly, pharmacogenomic testing of patients in cardiovascular medicine is now entering clinical practice. The FDA has recently approved the pharmacogenetic testing of VKORC1 and CYP2C9 polymorphisms prior to warfarin therapy. Identifying poor responders or those at risk of bleeding with standard nomogram dosing may prevent drug related complications that account for a substantial proportion of morbidity in hospital patients.
It would be desirable and advantageous to have one or a combination of biomarkers which could be used to determine a subject's response to an antiplatelet agent, or the suitability of a subject to treatment with one or more antiplatelet agents using various doses and dose regimens. The present inventions provide such biomarkers and their use in methods to determine these phenotypic traits of a subject with respect to responses to antiplatelet drugs and drug treatment regimens.